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Recent advances in Mobile Edge Computing (MEC) technology make it feasible to use Base Stations (BSs) intelligently by network caching, popularity-based video streaming, and more. Additional computing resources on the edge node offer an opportunity to reduce network traffic on the backhaul links during peak traffic hours. More recently, it has been found in the literature that collaborative caching strategies between neighbouring BSs (i.e., MEC servers) make it more efficient to reduce backhaul traffic and network congestion and thus improve the viewer experience substantially. In this work, we propose a Reinforcement Learning (RL)\u2013based collaborative caching mechanism in which the edge servers cooperate to serve the requested content from the end-users. Specifically, this research aims to improve the overall cache hit rate at the MEC, where the edge servers are clustered based on their geographic locations. This task is modelled as a multi-objective optimization problem and solved using an RL framework. In addition, a novel cache admission and eviction policy is defined by calculating the priority score of video segments in the clustered MEC mesh network.<\/jats:p>","DOI":"10.1145\/3664613","type":"journal-article","created":{"date-parts":[[2024,5,11]],"date-time":"2024-05-11T11:09:15Z","timestamp":1715425755000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Collaborative Video Caching in the Edge Network using Deep Reinforcement Learning"],"prefix":"10.1145","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1317-2605","authenticated-orcid":false,"given":"Anirban","family":"Lekharu","sequence":"first","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Technology Guwahati, Guwahati, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8892-6904","authenticated-orcid":false,"given":"Pranav","family":"Gupta","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Technology Guwahati, Guwahati, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9038-8138","authenticated-orcid":false,"given":"Arijit","family":"Sur","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering, Indian Institute of Technology Guwahati, Guwahati, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8793-250X","authenticated-orcid":false,"given":"Moumita","family":"Patra","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Guwahati, Guwahati, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,6,17]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2017.2750180"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3359989.3365423"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3306309.3306322"},{"key":"e_1_3_1_5_2","first-page":"1","volume-title":"2019 IEEE Wireless Communications and Networking Conference (WCNC \u201919)","author":"Baccour Emna","year":"2019","unstructured":"Emna Baccour, Aiman Erbad, Amr Mohamed, Kashif Bilal, and Mohsen Guizani. 2019. 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Toward smart and cooperative edge caching for 5G networks: A deep learning based approach. In 2018 IEEE\/ACM 26th International Symposium on Quality of Service (IWQoS \u201918). IEEE, 1\u20136."},{"key":"e_1_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.1145\/954339.954341"},{"issue":"1","key":"e_1_3_1_32_2","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1109\/JIOT.2019.2945640","article-title":"Deep reinforcement learning for cooperative content caching in vehicular edge computing and networks","volume":"7","author":"Qiao Guanhua","year":"2019","unstructured":"Guanhua Qiao, Supeng Leng, Sabita Maharjan, Yan Zhang, and Nirwan Ansari. 2019. Deep reinforcement learning for cooperative content caching in vehicular edge computing and networks. 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